Novel Statistical Wideband MIMO V2V Channel Modeling using Unitary Matrix Transformation Algorithm

For efficiently investigating the statistical properties of wideband multiple-input multiple-output (MIMO) channels for vehicle-to-vehicle (V2V) communication scenarios, we propose a novel computationally efficient solution to estimate the parameters of the proposed channel model for different propagation delays in this paper. To be specific, we first introduce a Unitary transformation method to estimate the propagation delay of the proposed channel model for the first tap in the preliminary stage before the mobile transmitter (MT) and mobile receiver (MR) move. Then, we estimate the real-time angular parameters based on the estimated delay and moving time/directions/velocities of the MT and MR. Furthermore, we estimate the expressions of the real-time complex channel impulse responses (CIRs), which can be used to characterize the physical properties of the proposed channel model, by substituting the estimates of the time-varying AoD and AoA and model parameters into the complex CIRs. Numerical results of the channel characteristics fit the theory results very well, which validate that the proposed channel model is practical for characterizing the beyond fifth-generation (B5G) V2V communication systems.